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Hypothesis 03 · study · DVOL · 907 days

The fear index under the microscope

DVOL is the “bitcoin VIX”: a single index for how violent a market expects the coming month to be. Several confident claims circulate about it. We took 907 days of our own data (January 2024 — July 2026) and tested three of them — including the one that did not hold up.

Source: the daily DVOL archive for BTC and ETH from Deribit. Every number below is a direct measurement; where something is an estimate or a limitation, we say so plainly. This is a journal of decisions, not signals.

Question 1

Does extreme fear hold, or does it fade?

It fades — always

Question 2

Is a fear peak a price bottom?

Yes, but not a signal

Question 3

Is fear overpriced?

Yes, 74% of the time

Finding 1 · the main one

Extreme fear does not hold

The most common beginner’s mistake is to see a high DVOL and decide that “it will stay this way now”. The data says the opposite. Over 2.5 years bitcoin DVOL oscillated around a single value — roughly 50 — and it returned there every time, wherever it started from.

≈50
the average DVOL level the market always returned to (median 49.9)
~23 days
to travel half the way back to the mean from any level
−9.8
by that many points DVOL settled over the 30 days after the highest 10% of readings
BTC DVOL · oscillating around a mean of ≈50907 days · 2024–2026

In numbers it looks like this: after the calmest days (the lowest 10%) DVOL edged up; after the most anxious ones (the highest 10%, above ~61) it settled by 10 points in a month. The link “high today → high tomorrow” weakened evenly and predictably: over a week, over two, over a month, the memory of the peak melted away.

High volatility falls back to normal. Low volatility does not last either. Extremes do not hold.

Finding 2 · with an honest “but”

A fear peak coincides with a bottom. But it is not a timer

The second common belief is more attractive: “buy when everyone is afraid”. We tested it literally — whether the highest fear readings really coincide with a price bottom. Partly, yes.

66%
of BTC fear peaks sat within two weeks of a local price bottom
84%
the same coincidence for Ethereum — panic is louder near the floor
≈ 50/50
bitcoin’s return 30 days after a peak — no better than usual

⚖ Why this is not a buy signal

Here hides the trap most sites keep quiet about. That it was a bottom only becomes known two weeks later — in hindsight. At the moment of a fear peak you do not know whether it is the floor or an intermediate stop before a deeper fall. And most importantly: thirty days after a peak, bitcoin’s return was statistically indistinguishable from any other day. Panic shows where the market broke — but not when to act. We show this coincidence honestly and immediately refuse to sell it as timing.

That is the difference between a journal and a signal service. A signal seller would take the “66%” figure and turn it into a promise. We put a second figure next to it — “after a month it is ≈ 50/50” — and leave you to add them up yourself.

Finding 3 · the cleanest

Fear costs more than the storms

The third test is the hardest of the three. DVOL shows which moves the market expects. We compared that expectation with what actually happened actually over the following 30 days — and counted how often the fear turned out to be exaggerated.

74%
of the time expected volatility was higher than actual — fear is overpriced
+9.5
by that many points on average the expectation exceeded reality (BTC)
877
days in the sample for this measurement — the largest of the three

In plain words: the market almost always pays more for insurance than it eventually turns out to cost. This is neither an anomaly nor our invention — it is a well-known risk premium the literature calls the “fear premium”. But reading about it is one thing; seeing it measured across 877 days of your own data is another. That gap between expectation and fact is the quiet engine behind half the strategies that sell volatility.

The expected move ≈ DVOL ÷ 19 per day. But the market consistently overpays for that expectation.

The limits of the study

What we know — and what we do not know

A study is honest exactly to the extent that its limits are named honestly. Here are ours:

⚖ Limitations we do not hide

  • One market era. 2.5 years is enough for a repeatable “fear returns to normal” (877 days of measurements), but it is one market regime. The next one may behave differently.
  • A panic coincidence is forensics, not statistics. Over 2.5 years there were only ~15 genuine fear peaks. On that count this is an observation, not a law.
  • A “local bottom” is only visible after the fact. The 66% figure relies on knowing the future — which is why it is a description, not an instruction for acting in real time.
  • A young project. We measure our own archive from the start of 2024; longer histories may add nuance. Past behaviour does not guarantee future behaviour.

Two of the three findings (the return to normal and overpriced fear) are solid and published as they are. The third (peak = bottom) we publish only inside this frame: as a description of capitulation, never as a signal.

One index. Three tests.
Zero promises.

We look at DVOL every morning — before almost anything else. It answers the question standing in front of every decision: is now the time to buy the move, or is insurance already too expensive? The live value and 2.5 years of history are on the volatility board.

Live DVOL now → The whole Case File of hypotheses
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